Т.А. Sergeyeva

1.7k total citations
40 papers, 1.4k citations indexed

About

Т.А. Sergeyeva is a scholar working on Analytical Chemistry, Spectroscopy and Bioengineering. According to data from OpenAlex, Т.А. Sergeyeva has authored 40 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Analytical Chemistry, 14 papers in Spectroscopy and 8 papers in Bioengineering. Recurrent topics in Т.А. Sergeyeva's work include Analytical chemistry methods development (21 papers), Analytical Chemistry and Chromatography (14 papers) and Mass Spectrometry Techniques and Applications (8 papers). Т.А. Sergeyeva is often cited by papers focused on Analytical chemistry methods development (21 papers), Analytical Chemistry and Chromatography (14 papers) and Mass Spectrometry Techniques and Applications (8 papers). Т.А. Sergeyeva collaborates with scholars based in Ukraine, United Kingdom and Germany. Т.А. Sergeyeva's co-authors include Sergey A. Piletsky, A. V. El’skaya, L. M. Sergeeva, Оleksandr Brovko, Elena Piletska, T. L. Panasyuk, E. V. Piletskaya, Alexandre Rachkov, Uwe Schedler and Heike Matuschewski and has published in prestigious journals such as SHILAP Revista de lepidopterología, Macromolecules and Journal of Chromatography A.

In The Last Decade

Т.А. Sergeyeva

40 papers receiving 1.3k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Т.А. Sergeyeva 782 518 348 341 301 40 1.4k
Álvaro García‐Cruz 589 0.8× 401 0.8× 398 1.1× 186 0.5× 298 1.0× 34 1.2k
Kal Karim 1.3k 1.7× 611 1.2× 254 0.7× 752 2.2× 331 1.1× 52 1.9k
Ede Bodoki 299 0.4× 486 0.9× 294 0.8× 349 1.0× 381 1.3× 79 1.5k
Viola Horváth 832 1.1× 439 0.8× 327 0.9× 463 1.4× 292 1.0× 57 1.5k
Maciej Cieplak 711 0.9× 508 1.0× 370 1.1× 241 0.7× 441 1.5× 36 1.3k
M. R. Smyth 414 0.5× 291 0.6× 327 0.9× 265 0.8× 143 0.5× 38 1.0k
Rasha M. El Nashar 660 0.8× 358 0.7× 584 1.7× 276 0.8× 316 1.0× 91 1.6k
Saadat Rastegarzadeh 424 0.5× 242 0.5× 252 0.7× 173 0.5× 194 0.6× 49 1.1k
Xuguang Qiao 543 0.7× 279 0.5× 401 1.2× 226 0.7× 332 1.1× 46 1.3k
John O’Mahony 1.4k 1.9× 635 1.2× 227 0.7× 849 2.5× 275 0.9× 24 2.2k

Countries citing papers authored by Т.А. Sergeyeva

Since Specialization
Citations

This map shows the geographic impact of Т.А. Sergeyeva's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Т.А. Sergeyeva with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Т.А. Sergeyeva more than expected).

Fields of papers citing papers by Т.А. Sergeyeva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Т.А. Sergeyeva. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Т.А. Sergeyeva. The network helps show where Т.А. Sergeyeva may publish in the future.

Co-authorship network of co-authors of Т.А. Sergeyeva

This figure shows the co-authorship network connecting the top 25 collaborators of Т.А. Sergeyeva. A scholar is included among the top collaborators of Т.А. Sergeyeva based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Т.А. Sergeyeva. Т.А. Sergeyeva is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zaets, Iryna, Т.А. Sergeyeva, Lyudmila I. Khirunenko, et al.. (2025). Red Cabbage Anthocyanin-Loaded Bacterial Cellulose Hydrogel for Colorimetric Detection of Microbial Contamination and Skin Healing Applications. Polymers. 17(15). 2116–2116. 1 indexed citations
2.
Piletska, Elena, et al.. (2024). Validation of a smartphone-compatible MIP-based sensor for bisphenol A determination in wastewater samples. Analytical and Bioanalytical Chemistry. 416(29). 7121–7129. 1 indexed citations
3.
Sergeyeva, Т.А., et al.. (2022). Highly-selective and sensitive plasmon-enhanced fluorescence sensor of aflatoxins. The Analyst. 147(6). 1135–1143. 17 indexed citations
4.
Sergeyeva, Т.А., et al.. (2022). Rationally designed molecularly imprinted polymer membranes as antibody and enzyme mimics in analytical biotechnology. SHILAP Revista de lepidopterología. 3. 100070–100070. 11 indexed citations
5.
Sergeyeva, Т.А., Elena Piletska, Rostyslav P. Linnik, et al.. (2021). Validation of aflatoxin B1 MIP membrane-based smartphone sensor system for real sample applications. Biopolymers and Cell. 37(5). 346–356. 2 indexed citations
6.
Sergeyeva, Т.А., Elena Piletska, Rostyslav P. Linnik, et al.. (2019). Development of a smartphone-based biomimetic sensor for aflatoxin B1 detection using molecularly imprinted polymer membranes. Talanta. 201. 204–210. 112 indexed citations
7.
Sergeyeva, Т.А., Elena Piletska, Olga A. Zaporozhets, et al.. (2017). Fluorescent sensor systems based on nanostructured polymeric membranes for selective recognition of Aflatoxin B1. Talanta. 175. 101–107. 55 indexed citations
8.
Sergeyeva, Т.А., et al.. (2016). Biosensor system for detection of bisphenol A in aqueous solutions. 38(3). 261–266. 1 indexed citations
9.
Sergeyeva, Т.А., Elena Piletska, Sergey A. Piletsky, et al.. (2013). Colorimetric test-systems for creatinine detection based on composite molecularly imprinted polymer membranes. Analytica Chimica Acta. 770. 161–168. 49 indexed citations
10.
Солдаткін, О. О., et al.. (2013). Acetylcholinesterase-based conductometric biosensor for determination of aflatoxin B1. Sensors and Actuators B Chemical. 188. 999–1003. 42 indexed citations
11.
Sergeyeva, Т.А., et al.. (2012). Application of creatinine-sensitive biosensor for hemodialysis control. Biosensors and Bioelectronics. 35(1). 466–469. 24 indexed citations
12.
Sergeyeva, Т.А., et al.. (2009). Catalytic molecularly imprinted polymer membranes: Development of the biomimetic sensor for phenols detection. Analytica Chimica Acta. 659(1-2). 274–279. 85 indexed citations
13.
Sergeyeva, Т.А.. (2009). Molecularly-imprinted polymers as synythetic mimics of bioreceptors. 2. Applications in modern biotechnology. Biopolymers and Cell. 25(6). 431–444. 1 indexed citations
14.
Sergeyeva, Т.А., Оleksandr Brovko, Elena Piletska, et al.. (2006). Porous molecularly imprinted polymer membranes and polymeric particles. Analytica Chimica Acta. 582(2). 311–319. 62 indexed citations
15.
Piletsky, Sergey A., et al.. (2005). Molecularly imprinted polymer tyrosinase mimics.. The Ukrainian Biochemical Journal. 77. 67–78. 1 indexed citations
16.
Piletsky, Sergey A., et al.. (2005). Molecularly imprinted polymers--tyrosinase mimics.. PubMed. 77(6). 63–7. 3 indexed citations
17.
Piletsky, Sergey A., E. V. Piletskaya, Т.А. Sergeyeva, T. L. Panasyuk, & A. V. El’skaya. (1999). Molecularly imprinted self-assembled films with specificity to cholesterol. Sensors and Actuators B Chemical. 60(2-3). 216–220. 104 indexed citations
18.
Sergeyeva, Т.А., et al.. (1999). β-Lactamase label-based potentiometric biosensor for α-2 interferon detection. Analytica Chimica Acta. 390(1-3). 73–81. 21 indexed citations
19.
Sergeyeva, Т.А., Nickolay V. Lavrik, Alexandre Rachkov, Z.I. Kazantseva, & A. V. El’skaya. (1998). An approach to conductometric immunosensor based on phthalocyanine thin film. Biosensors and Bioelectronics. 13(3-4). 359–369. 21 indexed citations
20.
Rachkov, Alexandre, et al.. (1994). Method and apparatus for the detection of the binding reaction of immunoglobulins. Sensors and Actuators B Chemical. 19(1-3). 610–613. 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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